The Limits of p-Hacking: Some Thought Experiments

Abstract

Suppose that the 300+ published asset pricing factors are all spurious. How much p-hacking is required to produce these factors? If 10,000 researchers generate eight factors every day, it takes hundreds of years. This is because dozens of published t-statistics exceed 6.0, while the corresponding p-value is infinitesimal, implying an astronomical amount of p-hacking in a general model. More structure implies that p-hacking cannot address $\approx$100 published t-statistics that exceed 4.0, as they require an implausibly nonlinear preference for t-statistics or even more p-hacking. These results imply that mispricing, risk, and/or frictions have a key role in stock returns.